Tests of Spatial Orientation (Card Rotations, Cube Comparisons) and Visualization (Form Board, Paper Folding, Surface Development) were administered to 537 (266 men, 268 women) university students. Participants rated the perceived difficulty of each of the tests on a 9 point scale ranging from 1 = very easy to 9 = very difficult. They were asked to indicate which of six problem solving strategies they used to solve the items on any particular test. The strategy statements were designed to tap part or whole problem solving strategies. Part strategies involved concentrating on salient aspects of a stimulus while whole strategies involved concentrating on an entire stimulus. Since men scored higher than women on all five tests analyses were performed separately for the sexes. For both men and women the first principal component accounted for more than 50% of the variance. Thus, previous findings of two spatial factors for men and one spatial factor for women were not supported. Problem solving strategy did not relate to performance on the spatial tests nor to difficulty ratings. There were no consistent sex differences in strategy except that women indicated that they guessed more on all tests. The limitations of introspective reports were discussed. For both men and women the perceived difficulty of a particular test correlated more highly with the total score on that test than with the total score on any other test. On the basis of this finding it was concluded that the difficulty index is a valuable one worthy of further study. The finding that men and women did not differ on mean difficulty rating on three of the tests, even though they differed significantly in performance on all tests, was interpreted to mean that each person subjectively rank orders the tests in terms of difficulty. It was hypothesized that the perceived difficulty of a test is, therefore, a function of the other tests included for study. There was moderate support for the hypothesis that, as the difference in rated difficulty for pairs of tests increases, the correlation between the two decreases. This was the case for six of 10 comparisons for men and three of 10 comparisons for women. It was suggested that this hypothesis would receive stronger support if tests of more distinct abilities were included in the same study. / Arts, Faculty of / Psychology, Department of / Graduate

In the last years a variety of open-source software packages focusing on visualization of human brain data have evolved. Many of them are designed to be used in a pure academic environment and are optimized for certain tasks or special data. The open source visualization system we introduce here is called OpenWalnut. It is designed and developed to be used by neuroscientists during their research, which enforces the framework to be designed to be very fast and responsive on the one side, but easily extendable on the other side. OpenWalnut is a very application-driven tool and the software is tuned to ease its use. Whereas we introduce OpenWalnut from a user's point of view, we will focus on its architecture and strengths for visualization researchers in an academic environment.

The stock market is a very complex and continuously changing environment in which many varying factors shape its growth and decline. Studying interesting trends and analyzing the intricate movements of the market, while ignoring distracting and uninteresting patterns has the potential to save large amounts of money for individuals as well as corporations and governments. This thesis describes research that was conducted with the goal to visualize stock market data in such a way that it is able to show how behavior and movement of various market entities affects the condition of the market as a whole. Different visualizations have been proposed, some that improve on existing traditional methods used by the Finance community and others that are novel in their layout and representation of data and interactions. The proposed design, by the use of interactive multiple coordinated views showing overviews and details of the stock market data using animated bubble charts and statistics, aims to enable the user to visualize market conditions that lead to the formation of a bubble in the market, how they lead to a crash and how the market corrects itself after such a crash. / Master of Science

The thesis addresses the problem of capturing and tracking multi-user interpretations of 3D spatial datasets. These interpretations are completed after the end of the visualization pipeline to identify and extract features of interest, and are subjective to human intuition and knowledge. Users may also assess regions of these interpretations. Consequently, the thesis proposes a provenance-enabled interpretation pipeline. It adopts and extends the W3C PROV data model, producing a provenance model for visual interpretations. This was implemented for seismic imaging interpretation in a proof-of-concept prototype architecture and application. Accumulation of users' interpretations and annotations are captured by the provenance model in a fine-grained form. The captured provenance information can be utilised to filter data. The work of this thesis was evaluated in three parts. First, a usability evaluation by geoscientists was conducted by postgraduate students in the field of geoscience to illustrate the system's ability in allowing users to amend others' interpretations and trace the history of amendments. Second, a conceptual evaluation of this research was approached by interviewing domain experts. The importance of this research to the industry was assured. Interviewees perceived and shared potential implementations of this work in the workflow of seismic interpretation. Limitations and concerns of the work were highlighted. Third, a performance evaluation was conducted to illustrate the behaviour of the architecture on commodity machines as well as on a multi-node parallel database, such that a new functionality in fine-grained provenance can be implemented simply but with an acceptable performance in realistic visualization tasks. The measures suggested that the current implementation achieved an acceptable performance in comparison to conventional methods. The proposed provenance model in an interpretation pipeline is believed to be a promising shift in methods of data management and storage which can record and preserve interpretations by users as a result of visualization. The approach and software development in this thesis represented a step in this direction.

Situations like war, terrorist attacks, fire accidents, floods, storms, etc., which threaten human life and property, demand immediate action to decrease the damage caused by them. A system is needed that predicts the future events based on what has happened and notifies the concerned personnel. The situation could be better understood in less time if the data is represented as colored, shaded and moving images rather than as numbers. Such a system requires a real-time Web-based visualization system with easy and secure access to grid resources, presenting easy-to-read graphics through a simple interface provided by a Web browser, and responding to user actions immediately. The Web and grid environments impose severe performance constraints such as communication time, latency of the network, etc., making it highly difficult to have a highly responsive real-time visualization. This work aims in finding an appropriate design that satisfies the above requirements. It also aims in understanding the limitations of a distributed environment for real-time applications and finding ways to overcome those limitations. A three-tier architecture is proposed, implemented, and tested to find the bottlenecks of the distributed environment. Relevant design principles are applied to a case study eliminating or minimizing the bottlenecks until the case study system satisfies all the requirements. The case study is the Fire-Smoke system, simulating the propagation of fire in the ex-USS Shadwell test area emulating a submarine. This system is re-implemented from a stand-alone system in OpenGL to a real-time Web-based visualization system using Java3D and J2EE technologies.

Rapid growing volumes of data demands new solutions in terms of analysing and visualizing. The growing amount of data contains valuable information which organizations in a more digitized society need to manage. It is a major challenge to visualize data, both in a static and interactive way. Through visualization of big data follows several opportunities containing risk assessment and decision basis. Previous research indicates a lack of standards and guidelines considering the development of interactive dashboards. By studying factors of success from a user-centered perspective we proceeded with a qualitative approach using semi-structured interviews. In addition to this we performed a thorough examination of existing literature in this particular field of research. A total of eight interviews were held, all eight respondents had experience from using or developing dashboards. The results indicates that user experience is an important yet not a sufficiently used principle. They also indicates challenges concerning the management of big data and particularly visualizing it. The results developed into a model which illustrates guidelines and vital components to orchestrate when developing a dashboard. A user-centered approach should pervade the entire developing process. Interactive functionalities are rather a necessity than a recommendation. With interactiveness comes drill-down functionalities which leads to a more intuitively practice. User experience is an essential component of the model, bringing light to individual customisations as well as it makes allowances to a large target group. The last component highlights the importance of early prototyping and an iterative approach to software development. The conclusion of the study is our complete model which brings opportunities to transform big data to great knowledge.

The primary goal of this research is to use eye-tracking in the development and usability evaluation of an e-learning tool called "Problem Solving Environment for Continuous Process Design" (PSE). The PSE is meant to aid engineering students in learning the design processes of automated manufacturing systems. PSE is a user-interactive Flash application which gives the user an opportunity to virtually design an automated industrial process by manipulating the parameters associated with it. PSE is evaluated using eye-tracking experiments in which users' eye movements are tracked using camera and sensors to determine users' gaze direction and fixations. The data collected from the experiment is used to determine if use of visual cues improved the usability of the PSE. Results show that use of visual cues for gaze direction improved the usability of the PSE application, based on faster task completion times and improved navigability.

Information visualizations must often be custom programmed to support complex user tasks and database schemas. This is an expensive and time consuming effort, even when general-purpose visualizations are utilized within the solution. This research introduces the Snap visualization server and system architecture that addresses limitations of previous Snap-Together Visualization research and satisfies the need for flexibility in information visualizations. An enhanced visualization model is presented that formalizes multiple-view visualization in terms of the relational data model. An extensible architecture is introduced that enables flexible construction and component integration. It allows the integration of diverse data, letting users spend less time massaging the data prior to visualization. The web-based server enables universal access, easy distribution, and the ability to intermix and exploit existing components. This web-based software architecture provides a strong foundation for future multiple-view visualization development. / Master of Science

Information visualizations utilizing multiple coordinated views allow users to rapidly explore complex data spaces and discover complex relationships. Most multiple-view visualizations are static with regard to the views that they provide and the coordinations that they support. Despite significant progress in the field of Information Visualization and development of novel interaction techniques, user interfaces for exploring data have lacked flexibility. As a result, the vast quantities of information rapidly being collected in databases are underutilized and opportunities for advancement of knowledge are lost. This research proposes the central concept of visualization schemas based on the Snap-Together Visualization (Snap) model, analogous to the successful database concept of data schemas, which will enable dynamic specification of information visualizations for any given database without programming. Relational databases provide significant flexibility to organize, store, and manipulate an infinite variety of complex data collections. This flexibility is enabled by the concept of relational data schemas, which allow data owners to easily design custom databases according to their unique needs. We bring the same level of flexibility to visualization development through visualization schemas. Visualization Schemas is a conceptual model, user interface, and software architecture while Fusion is the implemented system that enable users to rapidly and dynamically construct personalized multi-view visualization workspaces by coordinating visualizations in ways unforeseen by the original developers. / Master of Science

As libraries collect more and more data, it is worth taking some time to analyze the data we collect and effectively present it. This article details how to use visualization to investigate trends and make compelling arguments with data.